Artificial Intelligence Using for Weather Forecasting

Authors(2) :-V. Ramesh, G. Raju

Weather forecasting is very a statistical measure than a binary decision. We have a tendency to will develop an intelligent weather predicting module since this has become a necessary tool. This tool considers measures like most temperature, minimum temperature and rain for a sampled period of days and is analyzed. An intelligent prediction based on the obtainable data is accomplished using machine learning techniques. The analysis and prediction are supported linear regression that predicts consequent day’s weather with smart accuracy. An accuracy of over ninetieth is obtained, supported the data set. Recent studies have mirrored that machine-learning techniques achieved higher performance than traditional statistical methods. Machine learning, a branch of computing has been established to be a robust technique for predicting and analyzing a given data set. The module plays an important role in agricultural, industrial and supply fields wherever the weather outlook is a crucial criterion.

Authors and Affiliations

V. Ramesh
Department, Assistant Professor , Sri Indu College of Engineering & Technology, Hyderabad, Telengana, India
G. Raju
CSE Department, Assistant Professor, Vaagdevi College of Engineering, Hyderabad, Telengana, India

Weather Forecasting, Machine Learning, Artificial Intelligence, Linear Regression

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 0000-00-00
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 933-937
Manuscript Number : CSEIT172677
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

V. Ramesh, G. Raju, "Artificial Intelligence Using for Weather Forecasting", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.933-937, May-June-2017.
Journal URL : http://ijsrcseit.com/CSEIT172677

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